Physics

Perspective (graphical)

Bandwidth (computing)

Homography

Mathematics

Projective space

Statistics

Distortion (music)

Naturalness

Artificial intelligence

Amplifier

Projective test

Computer science

Quantum mechanics

Image stitching

Computer vision

Telecommunications

IEEE Transactions on Image Processing

Results of image stitching can be perceptually divided into single-perspective and multiple-perspective. Compared to the multiple-perspective result, the single-perspective result excels in perspective consistency but suffers from projective distortion. In this paper, we propose two single-perspective warps for natural image stitching. The first one is a parametric warp, which is an incremental combination of the dual-feature-based as-projective-as-possible warp and the quasi-homography warp. The second one is a mesh-based warp, which is determined by optimizing a total energy function that simultaneously emphasizes different characteristics of the single-perspective warp, including alignment, distortion and saliency. A comprehensive evaluation demonstrates that the proposed warp outperforms some state-of-the-art warps in urban scenes, including APAP, AutoStitch, SPHP and GSP.

Single-Perspective Warps in Natural Image Stitching